code: def run(self, replies: List[str]):
      self.iteration_counter += 1
  
      # let's simulate a corrupt JSON with 30% probability by adding extra brackets (for demo purposes)
      if random.randint(0, 100) < 30:
          replies[0] = "{{" + replies[0]
  
      try:
          output_dict = json.loads(replies[0])
          self.pydantic_model.parse_obj(output_dict)
          print(
              f"OutputParser at Iteration {self.iteration_counter}: Valid JSON from LLM - No need for looping: {replies[0]}"
          )
          return {"valid": replies}
  
      except (ValueError, ValidationError) as e:
          print(
              f"OutputParser at Iteration {self.iteration_counter}: Invalid JSON from LLM - Let's try again.\n"
              f"Output from LLM:\n {replies[0]} \n"
              f"Error from OutputParser: {e}"
          )
          return {"invalid": replies, "error_message": str(e)}
  
file_path: haystack/examples/pipeline_loop_to_autocorrect_json.py
imports: import json
  import os
  from haystack import Pipeline
  from haystack.components.generators.openai import OpenAIGenerator
  from haystack.components.builders.prompt_builder import PromptBuilder
  import random
  from haystack import component
  from typing import Optional, List
  import pydantic
  from pydantic import BaseModel, ValidationError
  import logging
label_desc: Use image node_id 2 for calling the OutputParser obj's underlying member method code with example usage: obj.run(replies) and returns: dict, dict